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Clean Grid Vision: A U.S. Perspective - Chapter 5. Global Power Market Trends

The evolution of the electricity sector toward competitive modern markets is occurring over a long period and responding to rapid changes in technologies, business models, and other market factors. No reformed power market anywhere in the world looks the same today as it did a decade ago. Technology has enabled some of the evolution, but perhaps it is more important that people and institutions learn from experience how to make markets better over time. Governments still have an important role—not as the authority controlling prices, but as the authority safeguarding the integrity of the economic processes that create prices in response to supply and demand and ensure reliability and other objectives are met. More VRE resources will change market conditions, but they will not change market fundamentals. Prices provide important signals for new investments and how the grid operates—including new technologies and processes discussed elsewhere in this report. If poor market design or the exercise of market power by a large entity distort these signals, outcomes will cease to be efficient and the public will bear the additional cost. Fundamentally, prices reflect supply, demand, and the cost of technological options.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Synthesis of historical reservoir operations from 1980 to 2020 for the evaluation of reservoir representation in large-scale hydrologic models

Abstract. All the major river systems in the contiguous United States (CONUS) (and many in the world) are impacted by dams, yet reservoir operations remain difficult to quantify and model due to a lack of data. Reservoir operation data are often inaccessible or distributed across many local operating agencies, making the acquisition and processing of data records quite time-consuming. As a result, large-scale models often rely on simple parameterizations for assumed reservoir operations and have a very limited ability to evaluate how well these approaches match actual historical operations. Here, we use the first national dataset of historical reservoir operations in the CONUS domain, ResOpsUS, to analyze reservoir storage trends and operations in more than 600 major reservoirs across the US. Our results show clear regional differences in reservoir operations. In the eastern US, which is dominated by flood control storage, we see storage peaks in the winter months with sharper decreases in the operational range (i.e., the difference between monthly maximum and minimum storage) in the summer. In the more arid western US where storage is predominantly for irrigation, we find that storage peaks during the spring and summer with increases in the operational range during the summer months. The Lower Colorado region is an outlier because its seasonal storage dynamics more closely mirrored those of flood control basins, yet the region is classified as arid, and most reservoirs have irrigation uses. Consistent with previous studies, we show that average annual reservoir storage has decreased over the past 40 years, although our analyses show a much smaller decrease than previous work. The reservoir operation characterizations presented here can be used directly for development or evaluation of reservoir operations and their derived parameters in large-scale models. We also evaluate how well historical operations match common assumptions that are often applied in large-scale reservoir parameterizations. For example, we find that 100 dams have maximum storage values greater than the reported reservoir capacity from the Global Reservoirs and Dams database (GRanD). Finally, we show that operational ranges have been increasing over time in more arid regions and decreasing in more humid regions, pointing to the need for operating policies which are not solely based on static values.

Geology↗

A Technical and Economic Assessment of LWR Flexible Operation for Generation and Demand Balancing to Optimize Plant Revenue

With increased penetration of subsidized variable renewable energy (VRE) resources and competition from low natural gas prices, existing light water reactor (LWR) nuclear power plants (NPPs) are struggling to remain economically competitive. This work examines the potential economic competitiveness of various thermal energy storage (TES) technologies when coupled directly or indirectly with a NPP. To highlight their relative economic competitiveness, we contrast several energy storage solutions in stochastic dispatch optimization. We leverage data from recent work analyzing a range of TES technologies with varying capital costs, performance, and technology readiness level (TRL) to establish our case. We explore inserting these technologies into an electricity market with existing nuclear generation and large projected variable renewable energy (VRE) penetration. Although these technologies' projected capital costs may make them unlikely candidates in their current state, this analysis demonstrates a high-fidelity techno-economic analysis of energy storage. Furthermore, as the projected cost of energy storage technologies evolves, this analysis sets a precedent for similar future investigations. One region with projected trends that may be unfavorable for existing nuclear capacity is the New York Independent System Operator (NYISO) market. New York state’s baseload generation has been historically provided by fossil-fired and nuclear assets. However, amid economic pressures from subsidized VREs and low natural gas prices, the state has recently deactivated Indian Point nuclear power plant units 2 and 3. Furthermore, the state plans to meet its zero-emission generation target by 2040 by replacing fossil-fired capacity with significant investments in VRE resources like wind and solar photovoltaic (PV) and battery storage. Increased intermittent resource penetration lowers the baseload power requirement, adding further economic pressure to the state’s three remaining NPPs still in operation. With three NPPs still in operation in New York, this work analyzes potential economic benefits to NPPs on the New York grid when directly or indirectly coupled with various TES technologies. This work requires two modeling steps to analyze the potential economic benefits of various system configurations of the TES directly or indirectly coupled with nuclear. First, this analysis leverages capacity expansion modeling by experts at the Electric Power Research Institute (EPRI). Using their deterministic capacity expansion model, U.S. Regional Economy, Greenhouse Gas, and Energy (US-REGEN), EPRI analysts evaluated the capacity and generation evolution of the New York state energy market under four projection scenarios. These four projection scenarios were developed to represent the potential evolution of the capacity and generation in NYISO from 2015 to 2050 under various economic, technology, and policy constraints. The results from these capacity expansion models are then used as boundary conditions in the second modeling step. The second modeling step uses the Holistic Energy Resource Optimization Network (HERON) for a set of stochastic techno-economic analyses (STEAs) to investigate the potential increase in the economic viability of various configurations of the TES. With no current capacity expansion capabilities, HERON takes the data generated from US-REGEN for 2050 to generate synthetic load, solar, and wind data. Then HERON economically optimizes the capacity and dispatch of the various TES configurations. The potential economic benefit is the differential net present value (NPV) of the TES configurations from the no-TES baseline. As a stochastic techno-economic analysis package, HERON introduces uncertainty into the economic metrics, while US-REGEN trades resolution for reduced computational complexity. Using HERON also allows the modeling of direct thermal coupling, a feature not common in capacity and dispatch models. As expected, with high capital costs, the costs of introducing energy storage for all the technologies considered outweighed the potential economic benefit of this strategy for flexible plant operation. The benefit of this analysis is primarily in demonstrating a workflow that examines innovative solutions to increase NPP revenue via TES coupling. HERON’s stochastic capacity and dispatch optimization process used in this work has proven an effective tool in observing and evaluating the impact of introducing storage technologies in a grid energy system.

25 ENERGY STORAGE↗

The Foundational Industrial Energy Dataset (FIED): Open-Source Data on Industrial Facilities

The state of data on industrial energy use has co-evolved over several decades with the demands of industrial energy analysis. The most recent development - analysis in support of decarbonizing the industrial sector - has changed the characteristics of industrial data that are useful for analysts and model developers. Although data and its collection processes may be cast from a conventional viewpoint as objective and free from the influence of social dynamics, this provides an incomplete picture of not only the processes by which information is generated, but also the limitations and opportunities of data to be useful for analysis. The foundational industry energy data set (FIED) is a result of the confluence of trends in open data and the demand for higher resolution industrial energy analysis. The general approach to compiling the FIED involves accessing, filtering, and formatting data published by federal organizations on the Internet for public use. Unlike most industrial energy datasets, which are published by the U.S. Energy Information Administration (EIA), the FIED relies on core datasets from the U.S. Environmental Protection Agency (EPA). The FIED addresses several of the areas of growing disconnect between the demands of industrial energy analysis and the state of industrial energy data by providing unit-level characterization - including estimates of energy use, greenhouse gas emissions, and design capacities - for facilities that are identified by latitude and longitude. This enables local-level analysis of existing combustion equipment, as well as regional comparisons with traditional industrial energy data estimates. The report summarizes the general logic behind compiling the FIED. The FIED itself and its Python code are available from OpenEI and GitHub, respectively.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Supply Chain for Photovoltaics in the United States: 2024 in Review

Solar photovoltaic (PV) and battery energy storage system (BESS) technologies are two immediately available options for meeting U.S. electricity demands, which are increasing due to expansion of loads from end uses including data centers, buildings, vehicles, and factories. Globally, PV and BESS supply chains are dominated by products manufactured in China and elsewhere by Chinese companies. However, U.S. PV and BESS manufacturing have recently grown, with some capacity in each step of the PV supply chain, albeit not enough to currently meet demand with domestic manufacturing alone. This study analyzes U.S. PV supply chains and costs in 2024, for the crystalline silicon and cadmium telluride module supply chains. The full report additionally addresses the PV balance of system, inverter and BESS supply chains. The study concludes with an analysis of technology installation trends, government support for domestic manufacturing, manufacturing jobs, and the domestic content of PV systems installed in the United States in 2024.

14 SOLAR ENERGY↗

Managing Increased Electric Vehicle Shares on Decarbonized Bulk Power Systems

Transportation electrification and power sector decarbonization - the convergence of these two trends present a complex planning problem requiring realistic, region-specific modeling and analysis to ensure that both can happen rapidly and cost effectively. This project, funded through the U.S. Department of Energy's Vehicle Technologies Office, models the evolution of the U.S. bulk power system (through 2050) in response to large-scale EV charging across all on-road vehicle segments. We will assess the opportunity and value of demand-side flexibility (i.e., "smart" charging) for reducing energy costs, increasing renewable generation shares, and managing future EV loads on the bulk power system. Overall, this study aims to provide an improved understanding of least-cost solutions for managing EV load growth on the grid and will make high-resolution EV load data sets publicly available for further analysis.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗

The Demand-Side Resource Opportunity for Deep Grid Decarbonization

Technological innovations are creating a larger role for demand-side resources in electric grids. The rise of demand-side resources is occurring alongside the efforts to decarbonize grids. The confluence of these two trends has motivated research on the role of demand-side resources in grid decarbonization. Here, we synthesize the demand-side resource literature to develop a coherent and realistic vision for that role. We find that demand-side resources can supplement supply-side approaches to decarbonize grids more quickly and cost effectively. The role of demand-side resources is secondary to that of supply-side resources, and a critical analysis of tradeoffs is required whenever demand-side solutions substitute for supply-side solutions. Nonetheless, our review suggests that demand-side solutions can play a meaningful role, providing around 10%-30% of the resources required for deep decarbonization in domains such as energy, peak capacity, and deployed solar capacity. However, demand-side resources remain underutilized due to several solvable barriers. The urgency imposed by climate change requires that these barriers be addressed to fully realize the demand-side resource opportunity.

decarbonization↗

Power market models for the clean energy transition: State of the art and future research needs

As power systems around the world are rapidly evolving to achieve decarbonization objectives, it is crucial that power system planners and operators use appropriate models and tools to analyze and address the associated challenges. This paper provides a detailed overview of the properties of power market models in the context of the clean energy transition. We review common power market model methodologies, their readiness for low- and zero-carbon grids, and new power market trends. Based on the review, we suggest model improvements and new designs to increase modeling capabilities for future grids. The paper highlights key modeling concepts related to power system flexibility, with a particular focus on hydropower and energy storage, as well as the representation of grid services, price formation, temporal structure, and the importance of uncertainty. We find that a changing resource mix, market restructuring, and growing price uncertainty require more precise modeling techniques to adequately capture the new technology constraints and the dynamics of future power markets. In particular, models must adequately represent resource opportunity costs, multi-horizon flexibility, and energy storage capabilities across the full range of grid services. Moreover, at the system level, it is increasingly important to consider sub-hourly time resolution, enhanced uncertainty representation, and introduce co-optimization for dual market clearing of energy and grid services. Likewise, models should capture interdependencies between multiple energy carriers and demand sectors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Synergistic Anion and Solvent-Derived Interphases Enable Lithium-Ion Batteries under Extreme Conditions

Lithium-ion batteries (LIBs) face increasingly stringent demands as their application expands into new areas, including extreme temperatures and fast charging. To meet these demands, the electrolyte should enable fast lithium-ion transport and form stable interphases on electrodes simultaneously. In practice, however, improving one aspect often compromises another. For instance, the trend toward electrolytes forming anion-derived interphases typically reduces transport efficiency due to weak-solvating solvents. Here, we propose that instead of relying on anions to form the interphase, leveraging both solvents and anions to form interphases can potentially lead to a balancing point between robust interphase formation and effective ion transport. Guided by this design principle, 2,2-difluoroethyl ethyl carbonate (DFDEC) was identified as the promising solvent. With the new electrolyte using DFDEC as the major solvent and lithium bis(fluorosulfonyl) imide (LiFSI) as the salt, graphite||LiNi 0.8 Mn 0.1 Co 0.1 O 2 (NMC811) full cells are capable of fast charging and demonstrate long-term cycling stability with a cutoff voltage of 4.5 V. Notably, the battery shows a capacity retention of 84.3% after 500 cycles with an average Coulombic efficiency (CE) as high as 99.93%. This new electrolyte also enables stable battery cycling across a wide temperature range (-20 to 60 °C), with excellent capacity retention.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

cerf: A Python package to evaluate the feasibility and costs of power plant siting for alternative futures

Long-term electric power sector planning and capacity expansion is a key area of interest to stakeholders across a wide range of organizations because it helps in making informed decisions about investments in infrastructure within the context of potential future vulnerabilities under various natural and human stressors. Future power plant siting costs will depend on a number of factors including the characteristics of the electricity capacity expansion and electricity demand (e.g., fuel mix of future electric power capacity, and the magnitude and geographic distribution of electricity demand growth) as well as the geographic location of power plants. Electricity technology capacity expansion plans modeled to represent alternate future conditions meeting a set of scenario assumptions are traditionally compared against historical trends which may not be consistent with current and future conditions. We present the `cerf` Python package (a.k.a., the Capacity Expansion Regional Feasibility model) which helps evaluate the feasibility and structure of future, scenario-driven electricity capacity expansion plans by siting power plants in areas that have been deemed the least cost option while considering dynamic future conditions. We can use `cerf` to gain insight to research topics such as: 1) under what conditions future projected electricity expansion plans from models such as GCAM-USA are possible to achieve, 2) where and which on-the-ground barriers to siting (e.g., protected areas, cooling water availability) may influence our ability to achieve certain expansions, and 3) how electricity infrastructure build-outs and value may evolve into the future when considering locational marginal pricing (LMP) based on the supply and demand of electricity from a grid operations model.

20 FOSSIL-FUELED POWER PLANTS↗

Water and Wastewater Annual Price Escalation Rates for Selected Cities Across the United States: 2023 Edition

This report builds on the 2016 Water and Wastewater Annual Price Escalation Rates for Selected Cities across the United States report prepared by Pacific Northwest National Laboratory (PNNL) for the U.S. Department of Energy’s (DOE) Federal Energy Management Program (FEMP). The 2017 report examined annual water and wastewater price escalation rate trends across the U.S. Annual water and wastewater price escalation rates are an important factor when conducting life-cycle cost analyses (LCCA) of water efficiency measures, which is required for Federal agencies. Following the framework of the 2017 report, PNNL used the American Water Works Association (AWWA) water and wastewater rate surveys to gather historical rate data for water and wastewater utilities in the US, which were used to calculate a sample set of water and wastewater annual price escalation rates (Figure E.1). An annual price escalation rate was calculated for 113 water utilities and 76 wastewater utilities that reported at least two AWWA surveys across the past 13 years (i.e., 2008 to 2021) and at least a five-year range between those two surveys. Statistical trends in the annual price escalation rates are also provided by the seven regions identified in Figure E.1. In the 2017 report, the average annual price escalation for the surveyed sample of water and wastewater rates were 3.0% and 3.2%, respectively. This report also calculated aggregate average annual price escalation rates for the surveyed sample of water and wastewater utilities to be 3.1% and 2.7%, respectively. These escalation rates were based on 87 water utilities and 46 wastewater utilities that reported data in at least two AWWA surveys with at least a five-year range between those two surveys and reported at least one AWWA survey in 2019 or 2021. Among water utilities, the highest average annual price escalation rate was 8.8%, and the highest average annual water de-escalation rate was -2.0%. And for wastewater utilities, the highest average annual wastewater price escalation rate was 10.2%, and the highest average annual wastewater de-escalation rate was -2.3%.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The Next Stage for Smart Cities: Metrics to Spur an Evolution from Technology for Efficiency to Technology for People's Needs

The Smart Cities movement is about a decade old, energized by the USDOT Smart Cities grant that sparked cities to dream big. Now, 10 years later, and multitudes of conferences and papers later, the biggest question regarding Smart Cities is whether any progress has been made? Smart Cities forums are typically led by the technology sector, either telecommunications, internet access, or most recently artificial intelligence (AI) concerns. Each of these areas have grown and found new applications in the context of Smart Cities, however, these technology applications are just tools toward ends. Do digital communications and assistance enable or foster improved access to real, tactile, non-virtual goods and services such as transportation, food, housing, trash removal, health care, education, social interaction? These and other topics are not 'big tech', but are each critical to quality of life outcomes and are day-to-day necessities, comprising many of the touch points through which citizens interact with municipal agencies. Regarding Smart Cities, relationships have not been fully refined as to how best to merge the emerging generation of technology and related trends with more mundane but essential requirements of tactile services. How should municipal managers and operators bring the range of new technology tools (e.g. on-demand transit, automated vehicles, digital connectivity) to bear to improve functions serving real- physical- non-virtual needs? How do we make cities more efficient in providing access to services and opportunities for improved quality of life? This paper examines the current Smart City movement, emerging trends, and the need to put metrics with respect to the delivery, access, and provision of real-life needs. Using a few case studies of past, present, and projected future scenarios, this paper attempts to bring Smart Cities into the real cities domain, perhaps pushing the moniker away from 'Smart' to 'Efficient' - something that can be measured, counted, and assessed. Through the consideration of the next stage of the evolution of cities from 'Smart' to 'Efficient', the combined efforts and experience of multiple researchers at the NREL and their network of collaborators highlights the need for updates metrics that can be used to start guiding efforts toward productive initiatives to improve quality of life.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Communities in energy transition: exploring best practices and decision support tools to provide equitable outcomes

Abstract The U.S. coal industry has been in a state of decline for the past decade, a trend ushered by flat electricity demand, increased regulatory pressure, and market competition from cost-competitive clean energy sources. The receding economic viability of the coal industry has been acutely felt by the communities with immediate economic ties to coal-fired generation. With the energy transition underway, the question of how to engage communities as stakeholders in the decision-making process and address their needs through an equitable and just transition remains unresolved. To that end, this paper explores the economic, environmental, and social challenges presented by the energy transition at the community level, highlighting four case studies from transitioning coal-dependent communities across the United States to ultimately identify best practices in coal plant decommissioning processes. This paper weaves these community-identified best practices into two support tools—a decommissioning checklist and a redevelopment decision-making framework—that can be used to engage communities in the power plant retirement decision, the site reclamation phase, and eventual redevelopment of the site and revitalization of the surrounding community.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Annual Supply Chain for Photovoltaics (ASC-PV) in the United States: 2024 in Review

This report analyzes U.S. PV and BESS supply chains and costs in 2024, for PV module and battery technologies, structural and electrical balance of system (BOS) components, as well as PV recycling. The report concludes with an analysis of technology installation trends, government support for domestic manufacturing, manufacturing jobs, and the domestic content of PV systems installed in the United States in 2024.

14 SOLAR ENERGY↗

Scaling Up Energy Efficiency Investment in Emerging Markets - Private Sector Perspectives

Since 2000, electricity demand has flattened and decoupled from Gross Domestic Product (GDP) growth in the Organization for Economic Cooperation and Development (OECD) countries. This trend is anticipated to continue for the next several decades and is largely attributed to the implementation of energy efficiency measures. However, non-OECD countries (emerging markets) have experienced, and are projected to continue experiencing, increasing electricity demands. If the world is to meet the requirements of the Paris Agreement, annual investments in clean energy and energy efficiency need to increase by a factor of six by 2050, compared to 2015. Information presented in this paper is based on qualitative and quantitative data collection and analysis methods to provide an empirical understanding of barriers to private sector clean energy investment including microgrid development, energy efficiency, smart grid development, and utility-scale wind and solar in emerging markets. Through literature review, a survey, and a series of webinar dialogues, USAID and the U.S. Department of Energy National Renewable Energy Laboratory (NREL) solicited input from private sector actors, including developers, project financiers, manufacturers and technical assistance service providers, on the challenges they face to market entry in emerging markets, and their suggestions for improving market competitiveness.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Trends and Effects of Changes in Business Cases for Petroleum Refineries

This study investigates trends and effects in business cases for petroleum refineries with a focus on effects for the state of Oregon for finished gasoline. Recently, the Oregon Department of Energy released the 2024 Oregon Energy Security Plan (ESP) which highlighted the reliance on out of state gasoline imports primarily from refineries located in the state of Washington. This study compiled a list of recent refinery closures in the United States and analyzed the drivers and impacts each refinery closure had to its respective region. The study dives into exploring three refinery closure business cases and past events that impacted gasoline prices in Oregon. Lastly, the paper outlines a potential framework of indicators to analyze the risk of future refinery closures based on the findings. This study hopes to inform stakeholders about the vulnerabilities in Oregon’s fuel supply chain and provide information that can guide strategic planning for future energy security.

02 PETROLEUM↗

The Transportation Energy and Mobility Pathway Options (TEMPO) Model: Overview and Validation of V1.0 [Slides]

This presentation documents the approaches and methods used in the Transportation Energy & Mobility Pathway Options™ (TEMPO) model to evaluate passenger and freight demand for transportation and mobility services, project vehicle ownership and technology adoption decisions, and determine transport mode choices to derive scenarios of future energy use and emissions. TEMPO is an all-inclusive transportation demand model that covers the entire United States, with an implicit spatial resolution and an hourly temporal resolution that allows for generating time-resolved energy use profiles to assess multisectoral integration aspects. Key features of the TEMPO model include the ability to perform endogenous out-of-sample forecasting to extrapolate recent emerging trends and analyze impacts of disruptive technological breakthroughs and behavioral changes. TEMPO employs an innovative representation of passenger mobility demand stemming from household-level decisions that determine vehicle adoption, ownership, and use based on sociodemographics (e.g., income, household composition), technology attributes (e.g., travel cost, time), geography (e.g., urban, suburban, rural) and population-specific multiday mobility and travel requirements. This representation enables a more forward-looking perspective on the use of new mobility options and the adoption of alternative fuel vehicles, as well as a more accurate representation of their energy usage profiles than previous modeling approaches. A comparison with the U.S. Energy Information Administration’s Annual Energy Outlook showcases the ability of TEMPO to accurately replicate widely accepted projections by representing the key elements of the entire transportation sector at the appropriate level of resolution. TEMPO is intended to generate future scenarios of technology adoption, energy use, and emissions in the transportation sector to compare alternatives, inform decision makers, and assess integration with energy infrastructure and supply systems at an appropriate spatiotemporal resolution.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Elucidation of Aromatic Catabolic Pathways in White-Rot Fungi

This project aims to investigate the hypothesis that white-rot fungi can simultaneously depolymerize lignin extracellularly and catabolize depolymerization products intracellularly as carbon and energy sources. Evaluating this hypothesis will provide deeper understanding of the role of white-rot fungi in facilitating carbon sequestration in Nature. Additionally, identifying the most promising fungal strains for lignin turnover and catabolism will catalyze future efforts in genetic tool development to enable metabolic engineering in white-rot fungi for lignin bioconversion to bioproducts. Lignin is the second most abundant plant-based biopolymer on Earth and represents up to 40% of the energy density of lignocellulosic biomass. Even though lignin is a massive natural carbon and energy reservoir, only a small group of basidiomycete fungi, namely white-rot fungi (WRF), have evolved the ability to efficiently depolymerize and mineralize lignin to CO2 and H2O. Considerable research efforts have been undertaken to understand how WRF depolymerize lignin but the biochemical reactions that convert lignin into CO2 have been largely neglected. In fact, it is unclear if WRF intracellularly catabolize lignin-derived aromatic compounds to utilize them as a carbon and energy source, or rather if lignin is depolymerized and mineralized extracellularly merely to facilitate access to cellulose and hemicellulose for use as a primary carbon source. To date, we have employed 13C-isotope labeling, systems biology approaches, and in vitro enzyme assays to definitively demonstrate that two WRF, Trametes versicolor and Gelatoporia (Ceriporiopsis) subvermispora, funnel carbon from lignin-derived aromatic compounds into central carbon metabolism via intracellular catabolic pathways [1]. Specifically, 13C-isotopic labeling approaches showed that these WRF utilize poplar-derived aromatic compounds (e.g. 4-hydroxybenzoic acid (4-HBA)) as a carbon source. In silico genome analysis led us to hypothesize a complete catabolic pathway for 4-HBA and identify multiple homologous sequences for enzymes with putative oxidative decarboxylase, hydroxylase, and ring-opening dioxygenase activities, which are among the main biochemical reactions acting on aromatic compounds. Spatial and differential proteomic and metabolomic analyses supported the proposed catabolic pathways and showed alternative catabolic steps in T. versicolor that were not present in G. subvermispora. Based on the in silico, proteomics, and transcriptomics results, we down-selected enzymes for further in vitro characterization, and we have assigned a function to six fungal enzymes (including oxidative decarboxylases, hydroxylases, and ring-opening dioxygenases). Interestingly, even though we selected homologous enzyme pairs from both WRF with similar -omics trends, in a few cases only one of the studied fungi showed activity for the proposed substrate. Based on all the observations from this study [1], we hypothesized that 4-HBA preferentially undergoes oxidative decarboxylation to hydroquinone and subsequent hydroxylation to 1,2,4-benzenetriol in G. subvermispora before ring cleavage, whereas 4-HBA would preferentially undergo hydroxylation to protocatechuate and further oxidative decarboxylation to 1,2,4-benzenetriol in T. versicolor. Examining additional decarboxylases and hydroxylases as well as enzymes from other protein families that can perform the same or similar oxidative reactions, such as cytochromes P450 with aromatic hydroxylation activity, will also be key for elucidating enzyme preferences for specific substrates. Overall, this work forms the foundation of a new research area based on lignin catabolism by WRF, which could be further exploited to convert the undervalued biopolymer lignin into value-added compounds.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗